[R-SIG-Finance] Anyone can help with backtesting?
sebastian.steins at gmail.com
Fri Mar 9 17:21:03 CET 2012
Anyway, what would be the way to implement such a strategy in quantstrat?
On Fri, Mar 9, 2012 at 5:13 PM, julien cuisinier
<j_cuisinier at hotmail.com> wrote:
> I do not know this package (so it could be brilliant) but I would go for
> quantstrat instead, seems more used / followed and hence less bug prone I
>> Date: Fri, 9 Mar 2012 15:38:02 +0100
>> From: sebastian.steins at gmail.com
>> To: r-sig-finance at r-project.org
>> Subject: [R-SIG-Finance] Anyone can help with backtesting?
>> I am currently trying to think about some investment strategies which
>> I want to backtest in R. So I found this toolbox as a great tool for
>> doing so:
>> However, since I am not that familiar with R and the way you create
>> the strategies in code, I am a bit confused on how to implement my
>> The idea is the following:
>> There are two basis modules of the portfolio, which should be weighted
>> about 40:60. To keep things simple at first, think of those modules as
>> of two strategies, the first one is the rotational trading strategy
>> (ranked by low volatility)[A], the second one is basically the same
>> strategy, but ranked by high performance[B].
>> After one year there should be done something specifically. At the
>> first day in any new year:
>> - if the overall profit of module A and B is greater than 0, positions
>> should be sold until the initial 4:6 ratio is reached again. The free
>> capital should then be invested in an fixed income ETF.
>> - if the overall profit of module A and B is less than 0, nothing
>> should be done.
>> - If there is any profit in the fixed income ETF, at the first day in
>> any year positions in the ETF should be closed, the free capital
>> should then be invested again in modules A, B according to their 4:6
>> Can you give me any hints on how to implement such a thing, with the
>> toolbox mentioned above or in any other way? At the moment I do not
>> even know how to start.
>> Thank you for your kind support!
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